Tire Rolling Resistance Estimation Using Pressure and Wear State
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Solution Overview
Problem
Conventional methods for estimating tire rolling resistance are inefficient due to the complexity of variables involved, such as speed, tire inflation pressure, and tread depth, making it difficult to accurately calculate rolling resistance in real-time, which affects fuel economy and range predictions.
Innovation Solution
A system and method that estimates rolling resistance using sensed tire inflation pressure and air temperature measurements, allowing for the generation of output signals representing the estimated rolling resistance force, which can be used to provide accurate fuel economy and range predictions without requiring complex variables, utilizing sensors mounted on the tire or external to it.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods use multiple variables (speed, tire inflation pressure, tread depth) to estimate rolling resistance, then measurement precision may be improved, but device complexity and computational requirements increase significantly
Solution Approach 1:
The patent extracts and eliminates unnecessary variables from the rolling resistance estimation process. Instead of using multiple variables (speed, tire inflation pressure, tread depth), the invention reduces the estimation to depend primarily on tire inflation pressure and temperature measurements, removing the complexity associated with measuring and processing multiple parameters simultaneously
Solution Approach 2:
The patent makes existing sensors serve multiple functions. Tire pressure monitoring system (TPMS) sensors, originally designed only for pressure measurement, are repurposed to provide both pressure and temperature data for rolling resistance estimation, eliminating the need for separate measurement systems and reducing overall device complexity
2Measurement precision
If conventional methods measure multiple variables in real-time, then rolling resistance estimation accuracy is improved, but productivity and real-time processing capability deteriorate due to computational inefficiency
Solution Approach 1:
The patent extracts and removes computationally intensive variables from the real-time processing requirement. By eliminating the need to process speed and tread depth data in real-time, and focusing only on pressure and temperature measurements, the system achieves accurate rolling resistance estimation with minimal computational burden, enabling real-time operation even on resource-constrained embedded systems
Solution Approach 2:
The patent performs preliminary characterization of tire behavior offline to create simplified lookup tables or empirical relationships. During real-time operation, the system only needs to query these pre-computed data structures based on current pressure and temperature readings, avoiding complex real-time calculations while maintaining accuracy
3Measurement precision
If conventional methods require vertical load measurement for rolling resistance calculation, then measurement precision is improved, but ease of operation deteriorates due to logistical difficulty
Solution Approach 1:
The patent extracts and eliminates the vertical load measurement requirement from the rolling resistance estimation process. By formulating the estimation method to depend only on tire inflation pressure and temperature, the invention removes the need for complex load cell installations or force sensor integration, making the system easy to implement using only standard TPMS sensors that are already present in modern vehicles
Data Source
AI summary
Systems (100) and methods (300) are disclosed herein for estimating, e.g., a rolling resistance force (242) acting upon a vehicle-mounted tire. An inventive model implements real-time signals (230) representative of sensed values for tire inflation pressure and/or contained air temperature, and selectively retrieved tire-specific steady state values (224), at least one of which corresponds to a wear state of the tire (222). Since the inflation pressure can be used instead of contained air temperature, the real time signals can be obtained from sensors (118) mounted on an inner liner of the tire, a sensor mounted on a valve of the tire, or even an external sensor wherein the inflation is indirectly obtained. The steady state values may initially be obtained using drum testing or finite element analysis, wherein current wear estimations (250) may further be provided in real time for adjustment of initial values (252) to improve model performance.